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20172025
most citedSemantically-Guided Representation Learning for Self-Supervised Monocular Depth

47 citations · 144 across the 47 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.CV2019★ 4 cited

Neural Outlier Rejection for Self-Supervised Keypoint Learning

Jiexiong Tang, Hanme Kim, Vitor Guizilini +2

Identifying salient points in images is a crucial component for visual odometry, Structure-from-Motion or SLAM algorithms. Recently, several learned keypoint methods have demonstra…

cs.CV2019

Self-Supervised 3D Keypoint Learning for Ego-motion Estimation

Jiexiong Tang, Rares Ambrus, Vitor Guizilini +4

Detecting and matching robust viewpoint-invariant keypoints is critical for visual SLAM and Structure-from-Motion. State-of-the-art learning-based methods generate training samples…

cs.CV2019★ 8 cited

Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances

Vitor Guizilini, Jie Li, Rares Ambrus +2

Dense depth estimation from a single image is a key problem in computer vision, with exciting applications in a multitude of robotic tasks. Initially viewed as a direct regression…

cs.CV2019★ 11 cited

Two Stream Networks for Self-Supervised Ego-Motion Estimation

Rares Ambrus, Vitor Guizilini, Jie Li +2

Learning depth and camera ego-motion from raw unlabeled RGB video streams is seeing exciting progress through self-supervision from strong geometric cues. To leverage not only appe…

cs.CV2019

3D Packing for Self-Supervised Monocular Depth Estimation

Vitor Guizilini, Rares Ambrus, Sudeep Pillai +2

Although cameras are ubiquitous, robotic platforms typically rely on active sensors like LiDAR for direct 3D perception. In this work, we propose a novel self-supervised monocular…